App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 9

Cross-scale state space semantic segmentation for high-resolution remote sensing imagery

Li Zhen
Wang Xiyuan
Liu Ziliang
College of Electronic and Electrical Engineering, Ningxia University, Yinchuan 750021, China
DOI: 10.19734/j.issn.1001-3695.2025.12.0530

Abstract

High-resolution remote sensing imagery exhibits significant scale variation and complex semantic distributions, which challenge existing semantic segmentation methods in preserving fine-grained structures and capturing multi-scale context. The study focuses on addressing these challenges by developing a lightweight cross-scale hierarchical fusion state-space network for semantic segmentation of high-resolution remote sensing scenes. The proposed network adopts a U-shaped architecture based on UNetMamba, integrates a global–local pyramid pooling mechanism to enhance multi-scale feature representation, and employs hierarchical collaborative fusion to improve semantic alignment and boundary reconstruction across layers. In addition, a learnable spline-assisted auxiliary supervision module is applied during training to strengthen detection of small objects and fine structural details without increasing inference complexity. Experimental evaluations on the ISPRS Vaihingen and Potsdam datasets show that the proposed approach outperforms representative state-of-the-art methods in terms of mIoU and mF1, demonstrating improved segmentation accuracy for small-scale categories and texture-rich regions while maintaining model efficiency.

Foundation Support

国家自然科学基金资助项目(42361056)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.12.0530
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 9

Publish History

[2026-06-02] Accepted Paper

Cite This Article

李臻, 汪西原, 刘子亮. 面向高分辨率遥感场景的跨尺度状态空间语义分割 [J]. 计算机应用研究, 2026, 43 (9). (2026-06-02). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0530. (Li Zhen, Wang Xiyuan, Liu Ziliang. Cross-scale state space semantic segmentation for high-resolution remote sensing imagery [J]. Application Research of Computers, 2026, 43 (9). (2026-06-02). https://doi.org/10.19734/j.issn.1001-3695.2025.12.0530. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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